Object discrimination is the process of taking radar measurements and creating a vector of probabilities that the object in track is a known object type. Prior attempts at object discrimination focused on ensuring that the largest probability would be assigned to the actual classification as often as possible and combined discrimination data using additive or multiplicative techniques which generally resulted in overconfident behavior. The probabilities were generally close to binary. As such, uncertainty in discrimination results was not represented within the classifications. Thus, a need exists in the art for improved object discrimination.